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Redis is a popular key-value store database used commonly across many enterprises. Based on the latest version of Redis 4.x, this book provides useful recipes to help you overcome any obstacle when it comes to the different tasks associated with Redis - from working with data types to administering and troubleshooting your Redis solution.

Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse.As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture options, workloads, and integration techniques for Big Data and the data warehouse. Part 3 deals with data governance, data visualization, information life-cycle management, data scientists, and implementing a Big Data–ready data warehouse. Extensive appendixes include case studies from vendor implementations and a special segment on how we can build a healthcare information factory.Ultimately, this book will help you navigate through the complex layers of Big Data and data warehousing while providing you information on how to effectively think about using all these technologies and the architectures to design the next-generation data warehouse.Learn how to leverage Big Data by effectively integrating it into your data warehouse. Includes real-world examples and use cases that clearly demonstrate Hadoop, NoSQL, HBASE, Hive, and other Big Data technologies Understand how to optimize and tune your current data warehouse infrastructure and integrate newer infrastructure matching data processing workloads and requirements

You receive an e-mail. It contains an offer for a complete personal computer system. It seems like the retailer read your mind since you were exploring computers on their web site just a few hours prior...As you drive to the store to buy the computer bundle, you get an offer for a discounted coffee from the coffee shop you are getting ready to drive past. It says that since you're in the area, you can get 10% off if you stop by in the next 20 minutes...As you drink your coffee, you receive an apology from the manufacturer of a product that you complained about yesterday on your Facebook page, as well as on the company's web site...Finally, once you get back home, you receive notice of a special armor upgrade available for purchase in your favorite online video game. It is just what is needed to get past some spots you've been struggling with...Sound crazy? Are these things that can only happen in the distant future? No. All of these scenarios are possible today! Big data. Advanced analytics. Big data analytics. It seems you can't escape such terms today. Everywhere you turn people are discussing, writing about, and promoting big data and advanced analytics. Well, you can now add this book to the discussion.What is real and what is hype? Such attention can lead one to the suspicion that perhaps the analysis of big data is something that is more hype than substance. While there has been a lot of hype over the past few years, the reality is that we are in a transformative era in terms of analytic capabilities and the leveraging of massive amounts of data. If you take the time to cut through the sometimes-over-zealous hype present in the media, you'll find something very real and very powerful underneath it. With big data, the hype is driven by genuine excitement and anticipation of the business and consumer benefits that analyzing it will yield over time.Big data is the next wave of new data sources that will drive the next wave of analytic innovation in business, government, and academia. These innovations have the potential to radically change how organizations view their business. The analysis that big data enables will lead to decisions that are more informed and, in some cases, different from what they are today. It will yield insights that many can only dream about today. As you'll see, there are many consistencies with the requirements to tame big data and what has always been needed to tame new data sources. However, the additional scale of big data necessitates utilizing the newest tools, technologies, methods, and processes. The old way of approaching analysis just won't work. It is time to evolve the world of advanced analytics to the next level. That's what this book is about.Taming the Big Data Tidal Wave isn't just the title of this book, but rather an activity that will determine which businesses win and which lose in the next decade. By preparing and taking the initiative, organizations can ride the big data tidal wave to success rather than being pummeled underneath the crushing surf. What do you need to know and how do you prepare in order to start taming big data and generating exciting new analytics from it? Sit back, get comfortable, and prepare to find out!

In the world of data science there are myriad tools available to analyze data. This book describes some of the popular software application tools along with the processes for downloading and using them in the most optimum fashion. --

This book shows you how to develop applications that work with Azure Cosmos DB. Azure and other cloud applications typically work with massive amounts of data that can be organized in different ways. These applications will often require elastic scale out of storage and throughput, and to work across new geographical regions. This is the.

Cut warranty costs by reducing fraud with transparent processes and balanced control Warranty Fraud Management provides a clear, practical framework for reducing fraudulent warranty claims and other excess costs in warranty and service operations. Packed with actionable guidelines and detailed information, this book lays out a system of efficient warranty management that can reduce costs without upsetting the customer relationship. You'll dig into the whole spectrum of warranty fraud, from simple sloppy procedures to systematic organized crime, and get to know the fraudulent parties, the victims, as well as the objectives and methods of the fraudulent activities in different scenarios. You'll learn how to implement controls to detect and reduce fraudulent claims and decrease the overall warranty costs. The impact of fraudulent claims is plainly spelled out alongside detailed descriptions of typical symptoms and process gaps present in diverse companies. A comprehensive, multi-modal framework for robust warranty management is presented as a template for revamping your own company's strategy. Fraudulent warranty claims occupy an estimated 3-15 percent of the average company's warranty costs, which generally average between 1-4 percent of sales. Many companies are unaware of the issue or struggle to take action against the claims for fear of upsetting business partners, or because they lack tangible evidence. This book details a robust warranty control framework that institutes transparency and control over the whole warranty chain—supporting the process far beyond just fraud reduction. * Understand the different actors (customers, sales channels, service agents, warranty providers, etc.) and different forms of warranty fraud * Uncover issues in your company's warranty processes * Learn methods to detect and prevent fraudulent activities * Implement a robust system of warranty cost control Warranty fraud is a major cost-control issue for most companies, but the sensitive nature of the topic leaves most reluctant to share their experiences and divulge their strategies. Warranty Fraud Management brings warranty fraud out into the open, and provides a clear, actionable framework for cost-savings through fraud reduction.

Defines the notion of an activity model learned from sensor data and presents key algorithms that form the core of the field Activity Learning: Discovering, Recognizing and Predicting Human Behavior from Sensor Data provides an in-depth look at computational approaches to activity learning from sensor data. Each chapter is constructed to provide practical, step-by-step information on how to analyze and process sensor data. The book discusses techniques for activity learning that include the following: * Discovering activity patterns that emerge from behavior-based sensor data * Recognizing occurrences of predefined or discovered activities in real time * Predicting the occurrences of activities The techniques covered can be applied to numerous fields, including security, telecommunications, healthcare, smart grids, and home automation. An online companion site enables readers to experiment with the techniques described in the book, and to adapt or enhance the techniques for their own use. With an emphasis on computational approaches, Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data provides graduate students and researchers with an algorithmic perspective to activity learning.

A hands on guide to web scraping and text mining for both beginners and experienced users of R * Introduces fundamental concepts of the main architecture of the web and databases and covers HTTP, HTML, XML, JSON, SQL. * Provides basic techniques to query web documents and data sets (XPath and regular expressions). * An extensive set of exercises are presented to guide the reader through each technique. * Explores both supervised and unsupervised techniques as well as advanced techniques such as data scraping and text management. * Case studies are featured throughout along with examples for each technique presented. * R code and solutions to exercises featured in the book are provided on a supporting website.

General practice computers have been widely used in the United Kingdom for the last 10 years and there are over 30 different systems currently available. The commercially available databases are based on two of the most widely used systems - VAMP Medical and Meditel. These databases provide both longitudinal and cross-sectional data on between 1.8 and 4 million patients. Despite their availability only limited use has been made of them for epidemiological and health service research purposes. They are a unique source of population-based information and deserve to be better recognized. The advantages of general practice databases include the fact that they are population based with excellent prescribing data linked to diagnosis, age and gender. The problems are that their primary purpose is patient care and the database population is constantly changing, as well as the usual problems of bias and confounding that occur in any observational studies. The barriers to the use of general practice databases include the cost of access, the size of the databases and that they are not structured in a way that easily allows analysis. Proper utilization of these databases requires powerful computers, staff proficient in writing computer programs to facilitate analysis and epidemiologists skilled in their use. If these structural problems are overcome then the databases are an invaluable source of data for epidemiological studies.

Data Model Patterns: A Metadata Map not only presents a conceptual model of a metadata repository but also demonstrates a true enterprise data model of the information technology industry itself. It provides a step-by-step description of the model and is organized so that different readers can benefit from different parts. It offers a view of the world being addressed by all the techniques, methods, and tools of the information processing industry (for example, object-oriented design, CASE, business process re-engineering, etc.) and presents several concepts that need to be addressed by such tools.This book is pertinent, with companies and government agencies realizing that the data they use represent a significant corporate resource recognize the need to integrate data that has traditionally only been available from disparate sources. An important component of this integration is management of the \"metadata\" that describe, catalogue, and provide access to the various forms of underlying business data. The \"metadata repository\" is essential to keep track of the various physical components of these systems and their semantics.The book is ideal for data management professionals, data modeling and design professionals, and data warehouse and database repository designers.A comprehensive work based on the Zachman Framework for information architecture—encompassing the Business Owner's, Architect's, and Designer's views, for all columns (data, activities, locations, people, timing, and motivation)Provides a step-by-step description of model and is organized so that different readers can benefit from different partsProvides a view of the world being addressed by all the techniques, methods and tools of the information processing industry (for example, object-oriented design, CASE, business process re-engineering, etc.)Presents many concepts that are not currently being addressed by such tools — and should be